Vision is traditionally tested by using a letter chart mounted on the wall 20 feet in front of a subject. The subject is asked to read the chart and assigned a vision score (often as a Snellen fraction such as 20/40). Normal vision is denoted as 20/20 (or 6/6 when metric units are used and the distance is 6 meters). Twenty feet (or 6 meters) is essentially infinity from an optical perspective. The Snellen score compares the distance the subject is able to see the target (20 feet, the numerator of the fraction) with the distance from which a normal seeing subject is able to identify the same target (40 feet or the denominator in the Snellen fraction).
LogMAR score (the logarithm of the minimum angle of resolution) is another commonly used scale. In this measurement system, the logarithmic Snellen scale is converted into a linear scale to measure visual acuity loss. 20/20 is converted to 0.0. Positive numbers indicate vision less than normal while negative numbers indicate better than normal visual acuity. LogMAR scores are more frequently used in scientific studies.
Greater accuracy in measuring a subject's ability to discern spatial differences can sometimes be achieved with other tests. For example, “vernier” acuity tests measure the ability to align two line segments. Contrast acuity measurement can also be useful. Typically, contrast acuity tests measure a subject's ability to discern a figure on a background under controlled illumination. Yet another known test of visual function is the “stereoscopic” acuity test, in which a subject is typically asked to detect an apparent depth difference between objects using both eyes.
For a long time clinicians have noted that subjects who score well on the standard vision tests continue to claim difficulties in vision. In other words, a subject is able to see 20/20 (LogMAR 0.0), but is not able to perform tasks that require normal vision. A clinical example would. be a patient who has cataracts and, although able to see well in a Doctor's office, is bothered by the glare of oncoming traffic at night. Such a condition can make the patient unable to drive at night—despite nominally “normal” vision.
Vision performance testing presents a number of challenges. While visual function is currently assessed in clinical and research settings by various measurements (e.g., visual acuity testing and contrast sensitivity testing), these measurements do not always provide an accurate indication of a subject's visual function in a practical sense. One drawback of these methods is that they typically test only one or two aspects of vision at a time (target size, percent contrast, and perhaps depth perception). Real world visual function consists of responding based on the multiple characteristics and simultaneous presentation of a visual target (e.g., size, percent contrast, motion or speed, color, etc.). Even if multiple individual visual tests are performed, each test is tailored to a specific aspect of vision, preventing a comprehensive assessment of vision performance from being obtained.
Even existing tests that attempt to evaluate visual function using representative activities of daily life have shortcomings. An example is testing vision performance using a driving simulator. The complexity of the apparatus often makes testing expensive, requiring subjects to travel to a particular location that may be remote from their physician's office. Additionally, the testing experience often includes tasks requiring more complex cognitive and physical function than simply vision. For example, in some driving simulators subjects must literally sit behind the wheel/windshield and operate controls in response to stimuli—this requires the coordination of visual processing and physical responses. Thus this testing scenario does not achieve a pure assessment of visual function.
Despite the currently available tests, there remains a need for vision performance measurements that are more consistent with real world function. Moreover, there is a need for intelligent testing systems that can help select the appropriate battery of tests for each subject and, in some instances, be able to modify the testing protocol in real time, based on initial testing results.